Książek K, Masarczyk W, Głomb P, Romaszewski M, Stokłosa I, Ścisło P, Dębski P, Pudlo R, Buza K, Gorczyca P et al..  2023.  The analysis of heart rate variability and accelerometer mobility data in the assessment of symptom severity in psychotic disorder patients using a wearable Polar H10 sensor. medXriv.

Głomb P, Cholewa M, Koral W, Madej A, Romaszewski M.  2023.  Detection of emergent leaks using machine learning approaches. Water Supply. 23(6)

Książek K, Masarczyk W, Głomb P, Romaszewski M, Stokłosa I, Ścisło P, Dębski P, Pudlo R, Gorczyca P, Piegza M.  2023.  HRV-ACC: a dataset with R-R intervals and accelerometer data for the diagnosis of psychotic disorders using a Polar H10 wearable sensor.

Gardas B, Głomb P, Sadowski P, Puchała Z, Jałowiecki K, Pawela Ł, Faucoz O, Brunet P-M, Gawron P, Van Waveren M et al..  2023.  Hyper-Spectral Image Classification Using Adiabatic Quantum Computation. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium.

Ciemięga A, Maresz K, Romaszewski M, Głomb P, Krupska-Wolas P, Prusik K.  2023.  Hyperspectral Imaging as a Facile and Non-Destructive Method for Size Analysis of Gold Nanoparticles Deposited on Porous Materials. Particle & Particle Systems Characterization.

Strzoda A, Grochla K, Głomb P, Madej A.  2023.  Link failure prediction in LoRa networks. International Wireless Communications and Mobile Computing Conference, IWCMC.

Głomb P, Romaszewski M, Cholewa M, Koral W, Madej A, Skrabski M, Kołodziej K.  2023.  Machine Learning for Water Leak Detection and Localization in the WaterPrime Project. Wojciechowski A.(Ed.), Lipiński P.(Ed.)., Progress in Polish Artificial Intelligence Research 4, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928..

Buza K, Książek K, Masarczyk W, Głomb P, Gorczyca P, Piegza M.  2023.  A Simple and Effective Classifier for the Detection of Psychotic Disorders based on Heart Rate Variability Time Series. Information Technologies – Applications and Theory 2023. 3498

Grochla K, Strzoda A, Marjasz R, Głomb P, Książek K, Łaskarzewski Z.  2022.  Energy-Aware Algorithm for Assignment of Relays in LPWAN. Transactions on Sensor Networks. 18(4)

Książek K, Głomb P, Romaszewski M, Cholewa M, Grabowski B, Buza K.  2022.  Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation. 21st International Conference on Image Analysis and Processing. 13231

Grabowski B, Głomb P, Książek K, Buza K.  2022.   Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering. Asian Conference on Intelligent Information and Database Systems. 1716

Romaszewski M, Głomb P, Sochan A, Cholewa M.  2021.  A dataset for evaluating blood detection in hyperspectral images. Forensic Science International. 320

Głomb P, Romaszewski M.  2020.  Anomaly detection in hyperspectral remote sensing images. Hyperspectral Remote Sensing: Theory & Applications.

Książek K, Romaszewski M, Głomb P, Grabowski B, Cholewa M.  2020.  Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks. Sensors. 20(Recent Advances in Multi- and Hyperspectral Image Analysis)

Romaszewski M, Głomb P, Sochan A, Cholewa M.  2020.  A Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set].

Masarczyk W, Głomb P, Grabowski B, Ostaszewski M.  2020.  Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling. Remote Sensing. 12(16)

Głomb P, Domino K, Romaszewski M, Cholewa M.  2019.  Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images. PP-RAI'2019. :p.121.

Cholewa M, Głomb P, Romaszewski M.  2019.  A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification. IEEE Geoscience and Remote Sensing Letters. 16:467-471.

Grabowski B, Głomb P, Romaszewski M, Ostaszewski M.  2019.  Unsupervised deep learning approach to hyperspectral anomaly detection. PP-RAI'2019.

Romaszewski M, Głomb P, Cholewa M.  2018.  Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data. Computer and Information Sciences.

Głomb P, Romaszewski M, Cholewa M, Domino K.  2018.  Application of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns. Forensic Science International. 290

Grabowski B, Masarczyk W, Głomb P, Mendys A.  2018.  Automatic pigment identification from hyperspectral data. Journal of Cultural Heritage. 31:1-12.

Cholewa M, Gawron P, Głomb P, Kurzyk D.  2017.  Quantum hidden Markov models based on transition operation matrices. Quantum Information Processing. 16:101.

Romaszewski M, Głomb P.  2016.  Parameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences. Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.

Głomb P, Cholewa M.  2016.  Performance of Interest Point Descriptors on Hyperspectral Images. Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP.